Class breakdown:
Homework: 15% (weekly, graded on completion)
Final Project: 25%
Midterm 1: 15% (average: mid 70s based on distribution?)
Midterm 2: 15% (average: low-mid 80s)
Final: 30% (out of 100 points, with possibility of 5 points added from extra credit video AND a bonus problem worth 5 points)

A: 93-100%
A-: 88-93%
B+: 83-88%
B: 78-83%
B-: 73-78%
C+: 68-73%
C: 63-68%
C-: >55-63%

I came into Chem 156 a little reluctant, despite being one of the rare biochem students who likes physical chemistry. I've never coded before, yet Dr. Rodriguez wanted us to complete a final project that required coding. And the first few weeks material can take time to wrap your head around, as it's statistical mechanics/thermodynamics and is a different way of thinking - you look at ensembles and distributions, not simply individual events and averages.

Although Dr. Rodriguez is very articulate, it was still hard to keep up and the lectures aren't podcasted. However, he was more than willing to compensate with extra office hours and slowing down the pace / reviewing the material if needed. I remember feeling quite lost at first with all the terminology and the complex examples but realizing later on that in the end - this is still modeled more like a physical chemistry class. Some of the examples are there to enrich your understanding and go beyond the scope of the exams. They're great examples - fascinating, but not all of them are worth losing sleep over and it becomes clearer over time what you must focus on to get the fundamentals down. Start there and build your way up to prevent yourself from getting overwhelmed!

The discussion / homework questions are also wonderful practice and mimic what is presented on the exams. Exams are a bit long and wording can sometimes be difficult to interpret, but the questions are very very fair and it is clear that Dr. Rodriguez wants us to succeed, which is encouraging. What makes him such a respectable professor is his desire for his students to succeed and willingness to accommodate - within reason. I believe it was this passion and genuine willingness to help that made the final project more bearable, as he was so earnest in providing ideas and suggestions when we would get stuck. He also gave extra credit for making a 3-minute video related to our final project, in addition to giving a pretty simple bonus problem on the final to help boost our grades.

All in all, a great class. I learned an extraordinary amount of material and there were so many applications to biochemistry/biophysics. I appreciate the knowledge I gained and am immensely grateful I had the chance to take this class with Jose.

Good prof and a great dude in general who respects and genuinely wants to teach his students. He's happy to answer any question, explain any confusing concept, etc. You can tell Jose knows what he's talking about and that he teaches based on what he finds interesting and important, not to check off requirement boxes. He mentions a lot of fun history-of-science and even brings up recently published research papers in his lectures.

He's pretty good at simplifying concepts to the essentials, but he's not always perfect at this and sometimes he words things in a confusing manner or uses unfamiliar terms to describe things. He's always willing to go back and reexplain though so it's very helpful to ask for clarification immediately if a question is worded in a weird way. One unfortunate thing about the class is that since it's 10 weeks long, he doesn't have time to cover a lot of topics with great depth and it shows. There's some info that he only mentions in a single slide or summarizes qualitatively without going into any specifics. On the upside this means that there's less tested material. (He allows you to bring a formula sheet for all exams.)

His exams are very fair and use questions that have some similarity to discussion and homework problems. Doing the discussion problems is as or more important than doing the homework, actually.

His class also has a portion that teaches you how to do some basic coding with python to model and graph things. There's a lot of help and resources for this though and Marcus Gallagher-Jones (who lectures the coding sessions) is even willing to read code and help with debugging. There's no need to get too crazy with the coding for the final project and a lot of people just ended up making some modifications to one of the types of models that we learn how to set up in lecture and applying the model to some kind of other problem.